Publications

Osses , A. & Varnet, L. (2023). Using auditory models to mimic human listeners in reverse correlation experiments from the fastACI toolbox. In , Turin, Italy.

Radushev, D. , Dogonasheva, O., Gutkin, B. & Zakharov, D. (2023). Chimera states in a ring of non-locally connected interneurons. In 7th Scientific School Dynamics of Complex Networks and their Applications (DCNA), Kaliningrad, Russian Federation, 229-232. doi:10.1109/DCNA59899.2023.10290318

Caucheteux, C. , Gramfort, A. & King, J. (2021). Disentangling syntax and semantics in the brain with deep networks. , Vol. 139: In International Conference on Machine Learning, PMLR, 1336-1348.

Dogonasheva, O., Gutkin, B. & Zakharov, D. (2021). Calculation of travelling chimera speeds for dynamical systems with ring topologies. In 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 61-64. doi:10.1109/DCNA53427.2021.9586903

Osses , A. & Varnet, L. (2021). Consonant-in-noise discrimination using an auditory model with different speech- based decision devices. In DAGA, Vienna Austria.

Zakharov, D., Dogonasheva, O. & Gutkin, B. (2021). Bistability of globally synchronous and chimera states in a ring of phase oscillators coupled by a cosine kernel. In 2021 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 211-214. doi:10.1109/DCNA53427.2021.9586968

Thoret, E., Andrillon, T., Gauriau, C., Léger, D. & Pressnitzer, D. (2020). Sleep deprivation impacts speech spectro-temporal modulations. In e-FA2020 (e- Forum Acusticum 2020 ), Lyon, France.

Zakharov, D., Dogonasheva, O. & Gutkin, B. (2020). Role of Pyramidal Cell M-current in Weak Pyramidal/Interneuronal Gamma Cluster Formation. In 2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR), Innopolis, Russia, IEEE. doi:10.1109/DCNAIR50402.2020.9216942

Bourgeois-Gironde, S., Mari, A., Nicolas, D. & Blunier, D. (2019). Grammatical mood and ambiguity aversion. In Proceedings of 10th International Conference of Experimental Linguistics, Lisbon, Portugal, 33-36. doi:10.36505/ExLing-2019/10/0008/000370

Castro, V. , Clodic, A., Alami, R. & Pacherie, E. (2019). Commitments in Human-Robot Interaction. In AI-HRI 2019 Proceedings. AAAI Fall Symposium Series.

Zuk, N. , Di Liberto, G. & Lalor, E. (2019). Linear-nonlinear Bernoulli modeling for quantifying temporal coding of phonemes in brain responses to continuous speech. In 2019 Conference on Cognitive Computational Neuroscience, Berlin, Germany.

Caze, R., Humphries, M., Gutkin, B. & Schultz, S. (2013). A difficult classification for neurons without dendrites. In Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on, San Diego, CA, USA, IEEE, 215-218. doi:10.1109/NER.2013.6695910

Pacherie, E. & Castro, V. (2022). Robots and Resentment: Commitments, recognition and social motivation in HRI. Emotional Machines. Perspectives from Affective Computing and Emotional Human-Machine InteractionSpringer Fachmedien Wiesbaden

Berthommier, F. & Lorenzi, C. (2021). Implications of Physiological Mechanisms of Amplitude Modulation Processing for Modeling Complex Sounds Analysis and Separation. (pp. 12). doi:10.1201/9781003064183

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2021). Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models. Advances in Intelligent Systems and Computing (Vol. 1252, pp. 241-255). doi:10.1007/978-3-030-55190-2_19

Pressnitzer, D., Agus, T., Kang, H. , Graves, J. & Andrillon, T. (2021). Apprentissage de motifs sonores. In S. Samson, B. Tillmann, C. Jourdan, V. Brun (Eds.), Audition et Cognition Montpellier: Sauramps Medical

Bourgeois-Gironde, S. (2020). Le sourire de ma boulangère : sur le rôle des expressions faciales dans les transactions monétaires. In Claudia Senik (Eds.), Crise de confiance ? (pp. 213-230). Paris: La Découverte, "Recherche"

Butterfill , S. & Pacherie, E. (2020). Towards a blueprint for a social animal. In Fiebich, Anika (Eds.), Minimal Cooperation and Shared Agency (pp. 111-125).Springer . doi:10.1007/978-3-030-29783-1

Mylopoulos, M. & Pacherie, E. (2020). Self-Control as Hybrid Skill. In A. Mele (Eds.), Surrounding Self-Control (pp. 81-100). Oxford : Oxford University Press. doi:10.1093/oso/9780197500941.003.0005

Shamma, S. (2020). Temporal Coherence Principle in Scene Analysis. The Senses: A Comprehensive Reference (Second Edition) (Vol. 2, pp. 777-790).Elsevier. doi:10.1016/B978-0-12-809324-5.24252-1

Bourgeois-Gironde, S. (2019). Comment Managua fut vers 1979 le lieu d’un événement linguistique révolutionnaire. In ESKA (Eds.), Problèmes d'Amérique latine (Vol. 112, pp. 101-114). doi:0.3917/pal.112.0101

Dumont, G., Maex, R. & Gutkin, B. (2018). Dopaminergic Neurons in the Ventral Tegmental Area and Their Dysregulation in Nicotine Addiction. In Alan Anticevic and John D. Murray (Eds.), Computational Psychiatry: Mathematical Modeling of Mental Illness (pp. 47-84). doi:10.1016/B978-0-12-809825-7.00003-1

Bourgeois-Gironde, S. (2017). How regret moves individual and collective choices towards rationality. Handbook of Behavioural Economics and Smart Decision-Making: Rational …

Gutkin, B. (2015). Theta-neurons. In Springer Verlag (Eds.), Encyclopedia of Comptutational Neuroscience (pp. 1034-1042).

Kuznetsov, A. & Gutkin, B. (2015). Dopaminergic cell Models. The Encyclopedia of Computational Neuroscience (pp. 2958-2965).

Remme, M., Lengyel, M. & Gutkin, B. (2015). Trade-off between dendritic democracy and independence in neurons with intrinsic subthreshold membrane potential oscillatio. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Remme, M., Lengyel, M. & Gutkin, B. (2014). Phase Response Methods in Dendritic Dynamics. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

Caze, R., Humphries, M. & Gutkin, B. (2013). Dendrites enhance both single neuron and network computation. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Graupner, M. & Gutkin, B. (2012). Dynamical Approaches to understanding cholinergic control of nicotine action pathways in the dopaminergic reward circuits. Computational Neuroscience of Drug Addiction (Springer ed.).Ahmed and Gutkin (eds.)

Pacherie, E. (2012). The Phenomenology of Joint Action: Self-Agency Vs. Joint-Agency . (pp. 343-389).